Despite recent biomedical breakthroughs and large genomic studies growing momentum, the Middle Eastern population, home to over 400 million people, is under-represented in the human genome variation databases. Here we describe insights from phase 1 of the Qatar Genome Program with whole genome sequenced 6,047 individuals from Qatar. We identified more than 88 million variants of which 24 million are novel and 23 million are singletons. Consistent with the high consanguinity and founder effects in the region, we found that several rare deleterious variants were more common in the Qatari population while others seem to provide protection against diseases and have shaped the genetic architecture of adaptive phenotypes. These results highlight the value of our data as a resource to advance genetic studies in the Arab and neighbouring Middle Eastern populations and will significantly boost the current efforts to improve our understanding of global patterns of human variations, human history and genetic contributions to health and diseases in diverse populations.

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,864 COVID-19 cases (713 with severe and 1,151 with mild disease) and 15,033 ancestry-matched population controls across 4 independent COVID-19 biobanks. We tested whether rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only 1 rare pLOF mutation across these genes among 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We found no evidence of association of rare LOF variants in the 13 candidate genes with severe COVID-19 outcomes.

Risk genes for Mendelian (single-gene) disorders (SGDs) are consistent across populations, but pathogenic risk variants that cause SGDs are typically population-private. The goal was to develop “QChip1,” an inexpensive genotyping microarray to comprehensively screen newborns, couples, and patients for SGD risk variants in Qatar, a small nation on the Arabian Peninsula with a high degree of consanguinity. Over 10⁸variants in 8445 Qatari were identified for inclusion in a genotyping array containing 165,695 probes for 83,542 known and potentially pathogenic variants in 3438 SGDs. QChip1 had a concordance with whole-genome sequencing of 99.1%. Testing of QChip1 with 2707 Qatari genomes identified 32,674 risk variants, an average of 134 pathogenic alleles per Qatari genome. The most common pathogenic variants were those causing homocystinuria (1.12% risk allele frequency), and Stargardt disease (2.07%). The majority (85%) of Qatari SGD pathogenic variants were not present in Western populations such as European American, South Asian American, and African American in New York City and European and Afro-Caribbean in Puerto Rico; and only 50% were observed in a broad collection of data across the Greater Middle East including Kuwait, Iran, and United Arab Emirates. This study demonstrates the feasibility of developing accurate screening tools to identify SGD risk variants in understudied populations, and the need for ancestry-specific SGD screening tools.

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,934 COVID-19 cases (713 with severe and 1,221 with mild disease) and 15,251 ancestry-matched population controls across four independent COVID-19 biobanks. We then tested if rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only one rare pLOF mutation across these genes amongst 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We find no evidence of association of rare loss-of-function variants in the proposed 13 candidate genes with severe COVID-19 outcomes.

Pharmacogenetic (PGx)‐informed medication prescription is a cutting‐edge genomic application in contemporary medicine, offering the potential to overcome the conventional “trial‐and‐error” approach in drug prescription. The ability to use an individual's genetic profile to predict drug responses allows for personalized drug and dosage selection, thereby enhancing the safety and efficacy of treatments. However, despite significant scientific and clinical advancements in PGx, its integration into routine healthcare practices remains limited. To address this gap, the Qatar Genome Program (QGP) has embarked on an ambitious initiative known as QPGx‐CARES (Qatar Pharmacogenetics Clinical Applications and Research Enhancement Strategies), which aims to set a roadmap for optimizing PGx research and clinical implementation on a national scale. The goal of QPGx‐CARES initiative is to integrate PGx testing into clinical settings with the aim of improving patient health outcomes. In 2022, QGP initiated several implementation projects in various clinical settings. These projects aimed to evaluate the clinical utility of PGx testing, gather valuable insights into the effective dissemination of PGx data to healthcare professionals and patients, and identify the gaps and the challenges for wider adoption. QPGx‐CARES strategy aimed to integrate evidence‐based PGx findings into clinical practice, focusing on implementing PGx testing for cardiovascular medications, supported by robust scientific evidence. The current initiative sets a precedent for the nationwide implementation of precision medicine across diverse clinical domains.

Background and Objective While standard doses of adjuvant fluoropyrimidine-based chemotherapies are generally safe for most patients, the risk of severe adverse drug reactions (ADRs) is increased for those with dihydropyrimidine dehydrogenase deficiency (DPYD), a genetic variation that affects drug metabolism. The objective of this study was to examine the cost effectiveness of offering DPYD pharmacogenetic-guided care, where genetic testing informs personalized dosing versus the current standard of care (SoC), which involves administering fluoropyrimidine-based therapies without prior genetic screening, for local or metastatic breast cancer patients in Qatar. Methods We developed a two-stage decision analysis, with an analytic tree model over a 6-month period, followed by a life-table Markov model over a lifetime horizon. We compared the current SoC with the alternate strategy of DPYD genetic screening in patients living in Qatar with local or metastatic breast cancer who were eligible for adjuvant fluoropyrimidine therapy. Clinical outcomes and utilities were obtained from published studies, while healthcare costs were estimated from Hamad Medical Corporation, Qatar. The short-term outcome included the incremental cost-effectiveness ratio (ICER), defined as cost per success (survival without grade III/IV ADRs) at 6 months. The long-term outcome was the ICER, defined as cost per quality-adjusted life year (QALY) gained, with a 3% annual discount rate. The study adopted a public healthcare perspective in Qatar. Sensitivity analyses were conducted to explore the impact of key input parameters on the robustness of the model. Results In the short-term model, at its base case, DPYD genomic screening was dominant over SoC with a mean cost-saving of QAR84,585 (95% confidence interval [CI], 45,270–151,657). This cost saving reflects the overall economic benefits associated with the implementation of DPYD genomic screening. In the long-term model, compared to the current SoC, DPYD genetic screening would result in an ICER of QAR21,107 (95% CI −59,382–145,664) per QALY gained. Conclusion Based on our model, implementing DPYD genetic screening to detect DPYD mutations in breast cancer patients before therapy initiation seems to be a cost-saving and cost-effective strategy in Qatar.